New Year '20 Offer
New Year '20 Offer
Predictive Modeling Training (2 Courses, 15+ Projects)
2 Online Course
15 Hands-on Projects
Verifiable Certificate of Completion
Predictive Modeling Training
Project on SAS - Predictive Modeling with SAS Enterprise Miner
Projects on ML - Predictive Modeling with Python
Project - Predictive Modeling using SPSS
Project - Predictive Modeling using Minitab
What you get
Mobile App Access
Predictive Modeling Training Course
This Online Predictive Modeling Course includes 2comprehensive Predictive Modeling courses, 15 Projects with 79+ hours of video tutorials and Lifetime Access. It is an amazing collection of practical and hands-on learning of the most updated training programs and projects in the area of predictive modeling using tools such as SAS, Minitab, SPSS. You will also get verifiable certificates (unique certification number and your unique URL) when you complete each of the 2 courses, 15 Projects. This course will help you learn to interpret data for statistical analysis.
Predictive modeling is a very important skill set to possess these days. With the advent of machine learning technologies and proliferation of data, the application of these techniques is increasing multifold and so the requirement for qualified professionals is also increasing.
This course on predictive modeling is, thus, a great learning resource for students and professionals who want to upskill themselves in the area of predictive modeling and machine learning. The course delivers more than 79+ hours of quality lectures which covers a wide area of predictive modeling such as introduction to predicting modeling and how various modeling techniques can be applied in different tools such as SAS, SPSS and Minitab. As the predictive analytics course covers three widely used tools as mentioned above, it caters to the need of a wide range of people who needs one or more of these tools to learn. The total number of videos in this predictive modeling course is about 280 and thus one can imagine the breadth and depth of the coverage of the subject. Each video lecture is designed to provide enough treatment on the subject without overwhelming the students.
Industry Growth Trend
[Source - MarketsandMarkets]
[Source - Indeed]
About Predictive Modeling Course
|Courses||No. of Hours|
|Predictive Modeling Training||2h 2m|
|Project on SAS - Predictive Modeling with SAS Enterprise Miner||9h 35m|
|Project - Predictive Modeling using SPSS||13h 12m|
|Projects on ML - Predictive Modeling with Python||9h 44m|
|Project - Predictive Modeling using Minitab||16h 11m|
|Project on EViews - Regression Modeling||3h 19m|
|Logistic Regression||1h 52m|
|Project - Logistic Regression with R||4h 25m|
|Project on ML - Predicting Prices using Regression||2h 21m|
|Project - Exploratory Data Analysis EDA using ggplot2, R and Linear Regression||2h 08m|
|Project - Logistic Regression using SAS Stat||4h 33m|
|Project - Linear Regression in Python||2h 15m|
|Project on Python Data Science - Predicting the Survival of Passenger in Titanic||2h 11m|
|Project - House Price Prediction using Linear Regression||2h 8m|
|Project - Credit Default using Logistic Regression||3h 9m|
|Project on R - Predictive Model for Term Deposit Investment||3h 12m|
|Project on R - Card Purchase Prediction||2h 31m|
|Course Name||Online Predictive Modeling Course Bundle|
|Deal||You get access to all 2 courses, 15 Projects bundle. You do not need to purchase each course separately.|
|Hours||79+ Video Hours|
|Core Coverage||Predictive modeling using tools such as SAS, Minitab, SPSS.|
|Course Validity||Lifetime Access|
|Eligibility||Anyone who is serious about learning predictive modeling and wants to make a career in Data/Statistical Analysis|
|Pre-Requisites||Basis Statistical concepts|
|What do you get?||Certificate of Completion for each of the 2 courses, 15 Projects|
|Certification Type||Course Completion Certificates|
|Verifiable Certificates?||Yes, you get verifiable certificates for each course with a unique link. These link can be included in your Resume/Linkedin profile to showcase your enhanced data analysis skills|
|Type of Training||Video Course – Self Paced Learning|
|Software Required||SPSS, Minitab, SAS, Microsoft Excel for practice|
|System Requirement||1 GB RAM or higher|
|Other Requirement||Speaker / Headphone|
Online Predictive Modeling Course Curriculum
In this section, each module of the Predictive Modeling training is explained briefly.
Here, we provide more details on the predictive modeling course content and explain at a very high-level what concepts will be covered under each course. This should give a fair understanding to the prospective students on what they can expect from this course and how useful will it be for their career goal.
|Sr. No.||Course Name||Course Duration||Course Description|
|1||Predictive Modelling training||2||This predictive modeling course is more than 2 hours long and here students learn about the introduction to predictive modeling, variables and its definition, steps involved in predictive modeling, smoothing methods, regression algorithms, clustering algorithms, neural network and support vector machines. Each concept is covered with enough examples and practice exercises. Basics of statistics and data visualization is also covered. Special emphasis is given to data preprocessing, data preparation, model evaluation, and deployment. Data distribution, data plotting, and charts, correlation vs causation, model interpretation, model improvement etc. are also covered in this module.|
|2||SAS – Predictive Modeling with SAS Enterprise Miner||9||This predictive modeling course is 9.5 hours long and is quite extensive. It covers topics such as PM SAS EM Introduction, PM SAS EM variable selection, SAS PM EM combination, SAS PM EM neural network, and SAS PM EM regression. It starts with an introduction to SAS and then gradually move towards topics such as selecting SAS tables, creating input data nodes, decision tree in SAS, creating score model, ROC chart, Neural network training, regression -table effect to name a few. This module covers everything that SAS includes for predictive modeling.|
|3||Predictive Modeling using Minitab||16||Minitab is another important tool for predictive modeling. This predictive modeling course on Minitab is about 16 hours long and covers topics such as Minitab and its application in predictive modeling, ANOVA using Minitab, Correlation techniques, regression modeling, predictive modeling using MS Excel. Under each of these heading, various small topics are covered. These are descriptive statistics, nonlinear regression, Anova, control charts etc. This module contains various case studies from finance and other domains to explain important concepts.|
|4||Predictive Modeling using SPSS||13||This module is more than 13 hours long and focuses on the implementation of predictive modeling using SPSS. SPSS is developed by IBM and is another widely used tool for predictive modeling. This predictive modeling course covers topics such as importing data to SPSS, correlation techniques, linear regression modeling, multiple linear regression, logistic regression, and multinomial regression. This course describes use cases from financial, pharmaceuticals and manufacturing domains and is very much suitable for students from these domains.|
|Total Duration||79+ Hours|
Certificate of Completion
What is Predictive Modeling?
Predictive modeling can be understood as the process of creation, test, and validation of a model. It uses concepts from statistics in predicting the outcomes. Predictive modeling contains a different set of methods like machine learning, statistics, artificial intelligence and so on. These models are made up of several predictors, also called attributes that are likely to impact future results. Predictive modeling is currently the most widely used in computer science, information technology, and information services domain.
This predictive modeling course targets to provide predictive modeling skills as mentioned above to business sectors/domains. Quantitative methods and predictive modeling concepts from this predictive modeling course could be extensively used in many fields to understand the current customer behavior, customer satisfaction, financial markets trends, studying effects of medicine in pharma sectors after drugs are developed and administered.
Minitab or SAS and SPSS are among the leading developers in the world towards building statistical analysis software. Across the world, these software’s are used by thousands of companies. These are also used by over 10000 universities and colleges for the purposes of research and teaching. Some major clients of Minitab, for example, consist of Pfizer, Royal Bank of Scotland, Nestle, Boeing, Toshiba, and DuPont.
Many independent studies conducted by companies like Mckinsey, Gartner, and others have predicted that data science, machine learning, and predictive modeling is going to be the biggest jobs of the 21st century and these professionals are going to be rewarded the best for it.
What tangible skills will I learn from this Predictive Modeling course?
This course covers many tangible skills that students can count on for the purpose of jobs and career switch. These skills are explained here to help students understand the value of this predictive modeling course.
- Skill to analyze data and see a complex pattern: data understanding and pattern extraction is a key skill for predictive modeling and a successful person in this domain should be able to make sense of data in no time. In this course, you will learn how to do that. You will be taught various types of data distribution, data patterns, and data understanding techniques. These skills will help you lifelong in making better and more intuitive decisions in all fields of work.
- Hands-on coding skill: – The predictive modeling course teaches three tools- Minitab, SAS, and SPSS. For that, this predictive modeling course is quite good. For predictive modeling and machine learning course one needs to be comfortable with coding, and hence having a sharp understanding of practical implementation is very important. This course teaches all these skills so that the student is industry ready and can comfortably work in real-life use cases.
- Strong understanding of concepts: – Machine learning concepts such as regression, classification, support vector machines, neural network, ROC curve, and many more concepts are taught which are frequently asked in interviews and which judges a candidate’s understanding of predictive modeling.
- There are some pre-requisites for this predictive modeling training course that must be fulfilled otherwise the understanding, of course, could become difficult for some students. Do not worry, the pre-requisite is not very difficult and almost anyone can qualify for that. If not, you can enroll for a bridge course or learn the pre-requisite first and then enroll for this predictive modeling course. These pre-requisites are: –
- Basic statistics understanding such as mean, median, mode, standard deviation is required. If you have forgotten these simple terms, you can revise your high school statistics class or see a couple of videos on YouTube. These concepts, however, will again be covered in this predictive modeling course, but some previous understanding is good to start with.
- Familiarity with excel is also a good thing. You will not learn excel but you will use excel data in Minitab, SPSS, and SAS too. So, some understanding of MS Excel is needed. If you know VBA tool-pack in excel then it is an added advantage, but not mandatory.
- Because machine learning is based on mathematics and hence it is good that you know the basics of linear algebra such as matrix and determinants, simple calculus like what is differentiation etc.
- Exposure to one programming language is necessary. If you have studied C or C++ in college that should be sufficient.
- This course is suitable for a wide range of audiences. In this section, we specifically explain this to ensure you know if you are suitable for this predictive modeling training.
- Students from technical or computer science fields are highly welcome, similarly, those from mathematics or statistics background is highly suitable. Most commonly students have a degree in B. Tech / BCA/ B.Sc./ MCA/ M. Sc/ M. Tech or MBA degree.
- Entry-level working professionals from the software field, banking, insurance, share market, information technologies who want to migrate to data analysis is also very suitable and they comprise a major chunk of our class size.
- The predictive modeling course is also suitable for managers and seasoned industry professionals who want to be a consultant or data scientist.
- People from engineering, biotechnology, law, medicine, theoretical computer science, geology, and ocean studies also take this predictive modeling training to do data analysis in their respective fields.
- Our past students have been Pharma and research scientists, Professionals of Equity Research and charted financial accountants, Quantitative and Predictive Modelers and Professionals from these domains.
Predictive Modeling Course FAQ’s
In this section, we list out some of the common questions frequently asked by students before enrolling for this course: –
Will this predictive modeling course teach me real-life scenarios of predictive modeling?
Yes. The predictive modeling course teaches all concepts with several live data from industry and explains many case studies in lecture. Thus, it is a very practical and actual real-life scenario. For example, it takes stock data and then explains how time series modeling can be done on it.
Is the field of predictive modeling in demand these days?
Predictive modeling is a lot in demand. Almost all IT companies are starting with Machine learning and hence they need trained people. Few years down the line, when all these companies will be established with ML, then they will already have enough ML people and hence the right time to learn this skill is NOW.
Will the predictive modeling training help me with practical skills or only theoretical knowledge?
The predictive modeling course covers both practical as well as a theoretical skill because both are important. It teaches three software tool Minitab, SPSS and SAS so you can understand that it is very practical as each example is demonstrated in this software.
How much time would I need to spend on this in a week?
Typically, you would need to spend 4-5 hours per week, but you can do more or less. As the predictive modeling course is self-paced that should not be a problem.
Will I be able to manage this predictive modeling course with a full-time job?
Time management is a personal thing and if you are determined for it, you can do so. We can say from our experience of teaching hundreds of students that it is possible and doable. As the predictive modeling course is self-paced and comes with a lifetime validity you can certainly manage with your job and other responsibilities.
Arranging columns in Asc Desc order01.43
Heart Pulse Study Continues10.34
Continue on Interpretation on Database08.31
- Many of our previous students have achieved great career success with this predictive modeling training course and realized their dream of becoming a data analyst and data scientist. Thus, you can very much rely on the career benefits and waste no time in the dilemma. Usually, career benefits come in one of the three terms below: –
- Job change: – You can switch to a more happening job after this course. As soon as you finish the predictive modeling course you can start attending interviews and look out of jobs. People usually become senior data analysts, associate data scientist, data scientist and data visualization expert after taking this predictive modeling course.
- Salary hike: – With a new job, you get better pay. Usually, such skills are paid higher compared to usual software jobs and hence you can expect up to 30-50% hike in your salary.
- Promotion: – if you show enough enthusiasm, you can get promoted in the current role, get more responsibility and raise the corporate ladder.
Job satisfaction is a great benefit from this field as happiness ratio is highest currently.
Lee Tze Hui
Completion of predictive modeling and implementation using excel.
SEYNI SOULEY BOUBACAR
Great refresher course